• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.683-694
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• 2003

We present X-tree Diff, a change detection algorithm for tree-structured data. Our work is motivated by need to monitor massive volume of web documents and detect suspicious changes, called defacement attack on web sites. From this context, our algorithm should be very efficient in speed and use of memory space. X-tree Diff uses a special ordered labeled tree, X-tree, to represent XML/HTML documents. X-tree nodes have a special field, tMD, which stores a 128-bit hash value representing the structure and data of subtrees, so match identical subtrees form the old and new versions. During this process, X-tree Diff uses the Rule of Delaying Ambiguous Matchings, implying that it perform exact matching where a node in the old version has one-to one corrspondence with the corresponding node in the new, by delaying all the others. It drastically reduces the possibility of wrong matchings. X-tree Diff propagates such exact matchings upwards in Step 2, and obtain more matchings downwsards from roots in Step 3. In step 4, nodes to ve inserted or deleted are decided, We aldo show thst X-tree Diff runs on O(n), woere n is the number of noses in X-trees, in worst case as well as in average case, This result is even better than that of BULD Diff algorithm, which is O(n log(n)) in worst case, We experimented X-tree Diff on reat data, which are about 11,000 home pages from about 20 wev sites, instead of synthetic documets manipulated for experimented for ex[erimentation. Currently, X-treeDiff algorithm is being used in a commeercial hacking detection system, called the WIDS(Web-Document Intrusion Detection System), which is to find changes occured in registered websites, and report suspicious changes to users.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.51-63
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• 2024

While the government policy to fully adopt BIM in the construction sector is being implemented, the construction and utilization of landscape BIM models are facing challenges due to problems such as limitations in BIM authoring tools, difficulties in modeling natural materials, and a shortage in BIM content including libraries. In particular, plants, fundamental design elements in the field of landscape architecture, must be included in BIM models, yet they are often omitted during the modeling process, or necessary information is not included, which further compromises the quality of the BIM data. This study aimed to contribute to the construction and utilization of landscape BIM models by developing a plant library that complies with BIM standards and is applicable to the landscape industry. The plant library of trees and shrubs was developed in Revit by modeling 3D shapes and collecting attribute items. The geometric information is simplified to express the unique characteristics of each plant species at LOD200, LOD300, and LOD350 levels. The attribute information includes properties on plant species identification, such as species name, specifications, and quantity estimation, as well as ecological attributes and environmental performance information, totaling 24 items. The names of the files were given so that the hierarchy of an object in the landscape field could be revealed and the object name could classify the plant itself. Its usability was examined by building a landscape BIM model of an apartment complex. The result showed that the plant library facilitated the construction process of the landscape BIM model. It was also confirmed that the library was properly operated in the basic utilization of the BIM model, such as 2D documentation, quantity takeoff, and design review. However, the library lacked ground cover, and had limitations in those variables such as the environmental performance of plants because various databases for some materials have not yet been established. Further efforts are needed to develop BIM modeling tools, techniques, and various databases for natural materials. Moreover, entities and systems responsible for creating, managing, distributing, and disseminating BIM libraries must be established.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2004.11a
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• pp.53-55
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• 2004

In emergency cases, such as the severe trauma involving the fracture of skull, spine, or cervical bone, from auto accident or a fall, and/or pneumothorax which can not be diagnosed exactly by the eye examination, it is necessary the radiological examination during transferring to the hospital for emergency care. The aim of this study was to design and evaluate the prototype of mobile medical image communication system based on CDMA 1X EVDO. The system consists of a laptop computer used as a transmit DICOM client, linked with cellular phone which support to the CDMA 1X EVDO communication service, and a receiving DICOM server installed in the hospital. The DR images were stored with DICOM format in the storage of transmit client. Those images were compressed into JPEG2000 format and transmitted from transmit client to the receiving server. All of those images were progressively transmitted to the receiving server and displayed on the server monitor. To evaluate the image quality, PSNR of compressed image was measured. Also, several field tests had been performed using commercial CDMA2000 1X-EVDO reverse link with the TCP/IP data segments. The test had been taken under several velocity of vehicle in seoul areas.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.12
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• pp.6-13
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• 2009

For X-band phased array systems, a power amplifier, a 6-bit phase shifter, a 6-bit digital attenuator, and a SPDT transmit/receive (T/R) switch are fabricated and measured. All circuits are demonstrated by using CMOS 0.18 um technology. The power amplifier has 2-stage differential and cascade structures. It provides 1-dB gain-compressed output power ($P_{1dB}$) of 20 dBm and power-added-efficiency (PAE) of 19 % at 8-11 GHz frequencies. The 6-bit phase shifter utilizes embedded switched filter structure which consists of nMOS transistors as a switch and meandered microstrip lines for desired inductances. It has $360^{\circ}$ phase-control range and $5.6^{\circ}$ phase resolution. At 8-11 GHz frequencies, it has RMS phase and amplitude errors are below $5^{\circ}$ and 0.8 dB, and insertion loss of $-15.7\;{\pm}\;1,1\;dB$. The 6-bit digital attenuator is comprised of embedded switched Pi-and T-type attenuators resistive networks and nMOS switches and employes compensation circuits for low insertion phase variation. It has max. attenuation of 31.5 dB and 0.5 dB amplitude resolution. Its RMS amplitude and phase errors are below 0.4 dB and $2^{\circ}$ at 8-11 GHz frequencies, and insertion loss is $-10.5\;{\pm}\;0.8\;dB$. The SPDT T/R switch has series and shunt transistor pairs on transmit and receive path, and only one inductance to reduce chip area. It shows insertion loss of -1.5 dB, return loss below -15 dB, and isolation about -30 dB. The fabricated chip areas are $1.28\;mm^2$, $1.9mm^2$, $0.34\;mm^2$, $0.02mm^2$, respectively.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.57-76
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• 2017

Recently, consumer needs are diversifying as information technologies are evolving rapidly. A lot of IT devices such as smart phones and tablet PCs are launching following the trend of information technology. While IT devices focused on the technical advance and improvement a few years ago, the situation is changed now. There is no difference in functional aspects, so companies are trying to differentiate IT devices in terms of appearance design. Consumers also consider design as being a more important factor in the decision-making of smart phones. Smart phones have become a fashion items, revealing consumers' own characteristics and personality. As the design and appearance of the smartphone become important things, it is necessary to examine consumer values from the design and appearance of IT devices. Furthermore, it is crucial to clarify the mechanisms of consumers' design evaluation and develop the design evaluation model based on the mechanism. Since the influence of design gets continuously strong, various and many studies related to design were carried out. These studies can classify three main streams. The first stream focuses on the role of design from the perspective of marketing and communication. The second one is the studies to find out an effective and appealing design from the perspective of industrial design. The last one is to examine the consumer values created by a product design, which means consumers' perception or feeling when they look and feel it. These numerous studies somewhat have dealt with consumer values, but they do not include product attributes, or do not cover the whole process and mechanism from product attributes to consumer values. In this study, we try to develop the holistic design evaluation model based on consumer values based on three-step approach from product attributes, perceived attributes, to consumer values. Product attributes means the real and physical characteristics each smart phone has. They consist of bezel, length, width, thickness, weight and curvature. Perceived attributes are derived from consumers' perception on product attributes. We consider perceived size of device, perceived size of display, perceived thickness, perceived weight, perceived bezel (top - bottom / left - right side), perceived curvature of edge, perceived curvature of back side, gap of each part, perceived gloss and perceived screen ratio. They are factorized into six clusters named as 'Size,' 'Slimness,' 'No-Frame,' 'Roundness,' 'Screen Ratio,' and 'Looseness.' We conducted qualitative research to find out consumer values, which are categorized into two: look and feel values. We identified the values named as 'Silhouette,' 'Neatness,' 'Attractiveness,' 'Polishing,' 'Innovativeness,' 'Professionalism,' 'Intellectualness,' 'Individuality,' and 'Distinctiveness' in terms of look values. Also, we identifies 'Stability,' 'Comfortableness,' 'Grip,' 'Solidity,' 'Non-fragility,' and 'Smoothness' in terms of feel values. They are factorized into five key values: 'Sleek Value,' 'Professional Value,' 'Unique Value,' 'Comfortable Value,' and 'Solid Value.' Finally, we developed the holistic design evaluation model by analyzing each relationship from product attributes, perceived attributes, to consumer values. This study has several theoretical and practical contributions. First, we found consumer values in terms of design evaluation and implicit chain relationship from the objective and physical characteristics to the subjective and mental evaluation. That is, the model explains the mechanism of design evaluation in consumer minds. Second, we suggest a general design evaluation process from product attributes, perceived attributes to consumer values. It is an adaptable methodology not only smart phone but also other IT products. Practically, this model can support the decision-making when companies initiative new product development. It can help product designers focus on their capacities with limited resources. Moreover, if its model combined with machine learning collecting consumers' purchasing data, most preferred values, sales data, etc., it will be able to evolve intelligent design decision support system.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.148-155
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• 2002

Multithreaded models improve the efficiency of parallel systems by combining inner parallelism, asynchronous data availability and the locality of von Neumann model. This model executes thread code which is generated by compiler and of which quality is given by the method of generation. But multithreaded models have the demerit that execution model is restricted to a specific platform. On the contrary, Java has the platform independency, so if we can translate from threads code to Java bytecode, we can use the advantages of multithreaded models in many platforms. Java executes Java bytecode which is intermediate language format for Java virtual machine. Java bytecode plays a role of an intermediate language in translator and Java virtual machine work as back-end in translator. But, Java bytecode which is translated from multithreaded models have the demerit that it is not secure. This paper, multhithread code whose feature of platform independent can execute in java virtual machine. We design and implement translator which translate from thread code of multithreaded code to Java bytecode and which check secure problems from Java bytecode.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.95-112
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• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.63-73
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• 2015

This work proposes a 2-channel time-interleaved (T-I) 10b 120MS/s pipeline SAR ADC minimizing offset mismatch between channels without any calibration scheme. The proposed ADC employs a 2-channel SAR and T-I topology based on a 2-step pipeline ADC with 4b and 7b in the first and second stage for high conversion rate and low power consumption. Analog circuits such as comparator and residue amplifier are shared between channels to minimize power consumption, chip area, and offset mismatch which limits the ADC linearity in the conventional T-I architecture, without any calibration scheme. The TSPC D flip-flop with a short propagation delay and a small number of transistors is used in the SAR logic instead of the conventional static D flip-flop to achieve high-speed SAR operation as well as low power consumption and chip area. Three separate reference voltage drivers for 4b SAR, 7b SAR circuits and a single residue amplifier prevent undesirable disturbance among the reference voltages due to each different switching operation and minimize gain mismatch between channels. High-frequency clocks with a controllable duty cycle are generated on chip to eliminate the need of external complicated high-frequency clocks for SAR operation. The prototype ADC in a 45nm CMOS technology demonstrates a measured DNL and INL within 0.69LSB and 0.77LSB, with a maximum SNDR and SFDR of 50.9dB and 59.7dB at 120MS/s, respectively. The proposed ADC occupies an active die area of 0.36mm2 and consumes 8.8mW at a 1.1V supply voltage.

• Korea Science and Art Forum
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• v.31
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• pp.21-32
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• 2017

Local festivals form the regional cultures and atmosphere of communication; they increase the demand of domestic tourism businesses and thus, have an important role in ripple effects (e.g. regional image improvement, tourist influx, job creation, regional contents development, and local product sales) and economic revitalization. IoT (Internet of Thing) technologies have been developed especially, beacon-one of the IoT services has been applied as plenty of types and forms both domestically and internationally. However, notwithstanding expansion of current digital mobile technologies, it still remains as difficult for the individual to track the information about all the local festivals and to fulfill the tourists' needs of enjoying festivals given the weak strategic approaches and advertisement activities. Furthermore, current festival-related mobile applications don't function well as delivering information and have numerous contents issues (e.g. ways of information delivery within the festival places, independent application usage for each festival, one time usage due to one time event). This research, based on the background mentioned above, aims to develop the local festival mobile application and data analysis system applying beacon technology. First of all, three algorithms were developed, namely, 'festival crowding algorithm', 'visitor stats algorithm', and 'customized information algorithm', and then beta test was followed with the developed application and data analysis system. As a result, they could form the database of visitors' types and behaviors, and provide functions and services, such as personalized information, waiting time for festival contents, and 'hot place' function. Besides, in Google Play store, they also got the titles given with more than 13,000 downloads within first three months and as the most exposed application related with festivals; and, thus, got credited with their marketability and excellence. This research follows this order: chapter 2 shows the literature review of local festival related with technology development, beacon service, and festival application. In Chapter 3, design plans and conditions are described of developing local festival mobile application and data analysis system with beacon. Chapter 4 evaluates the results of the beta performance test to verify applicability of the developed application and data analysis system, and lastly, chapter 5 explains the conclusion and suggests the future research.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.